This course trains you in the skills needed to program specific orientation and achieve precise aiming goals for spacecraft moving through three dimensional space. First, we cover stability definitions of nonlinear dynamical systems, covering the difference between local and global stability. We then analyze and apply Lyapunov's Direct Method to prove these stability properties, and develop a nonlinear 3-axis attitude pointing control law using Lyapunov theory. Finally, we look at alternate feedback control laws and closed loop dynamics.
After this course, you will be able to...
* Differentiate between a range of nonlinear stability concepts
* Apply Lyapunov’s direct method to argue stability and convergence on a range of dynamical systems
* Develop rate and attitude error measures for a 3-axis attitude control using Lyapunov theory
* Analyze rigid body control convergence with unmodeled torque

レビュー

Filled StarFilled StarFilled StarFilled StarHalf Faded Star

4.7 (29 件の評価)

5 stars

24 ratings

4 stars

3 ratings

2 stars

2 ratings

レッスンから

Attitude Control of States and Rates

A nonlinear 3-axis attitude pointing control law is developed and its stability is analyized using Lyapunov theory. Convergence is discussed considering both modeled and unmodeled torques. The control gain selection is presented using the convenient linearized closed loop dynamics.

講師

Hanspeter Schaub

Glenn L. Murphy Chair of Engineering, Professor

字幕

Hi, and welcome to this next module on Spacecraft Dynamics Control. Here, we're going to be talking about how to develop a fully three-axis attitude control development using Lyapunov theory and some of its properties. So, and particularly, in this development we care not only just about detumbling an object and bringing it to rest, but we want to bring it to rest pointing in a particular direction, called the regulation problem. And we'll develop it also in a more general formulation – a tracking formulation – where maybe your attitude isn't just fixed in inertial space, but you want to slowly follow an object in space. Let's say you're tracking space debris or you're flying over a planet and you want to look at a landmark on the planet, you'll have to continually adjust your heading so this is called a tracking problem and we'll be developing both formulations. Once we have this done, we can now look at some of the properties of this control and particularly what happens when you have gain selections in there, but also disturbances happening on the spacecraft. Especially, we look at external torques on model dynamics that come in there, and we can come up with predictions on what's gonna happen to the closed-loop dynamics.